I have a strong bias against injecting business logic into the stored procedures. It is not scalable, is hard to reuse, is a pain to test, has limited access to your class libraries, etc... However, I think there are some legit cases to put advanced T-SQL in a SP, but you're playing with fire.
Here are some reasons - basically either performance, functionality, or legacy constraints force you to.
- Aggregations, Joins, and Filters - If you need to sum up 1000 child rows, it's not feasible to return all that data to the app server and sum it in C#. Obviously using the SQL sum() function would be the better choice. Likewise, if your logic is part of a complex filter (say for a search page), it performs much faster to filter at the database and only pull over the data you need.
- Batch calls for performance - SQL Server is optimized for batch calls. A single update with a complex where clause will likely run much faster than 1000 individual updates with simple where clauses. For performance-critical reasons, this may force logic into the stored procedure. However, in this case, perhaps you can code-generate the SQL scripts from some business-rules input file, so you're not writing tons of brittle SQL logic.
- Database integration validation - Say you need to ensure that code is unique across all rows in the table (or for a given filter criteria). This, by definition, must be done on the database.
- Make a change to legacy systems where you're forced into using the SP - Much of software engineering is working with legacy code. Sometimes this forces you into no-win situations, like fixing some giant black box stored procedure. You don't have time to rewrite it, the proc requires a 1 line change to work how the client wants it, and making that change in the stored proc is the least of the evils.
- The application has no business tier - Perhaps this procedure is for a not for an N-tier app. For example, maybe it's for a custom report, and the reporting framework can only call stored procs directly, without any middle-tier manipulation.
- Performance critical code - Perhaps "special" code must be optimized for performance, as opposed to maintainability or development schedule. For example, you may have some rules engine that must perform, and being closer to the core data allows that. Of course, sometimes there may be ways to avoid this, such as caching the results, scaling out the database, refactoring the rules engine, or splitting it into CRUD methods that could be batched with an ORM mapping layer.
- Easy transactions - It can be far easier for a simple architecture to rollback a transaction in SQL than in managed code. This may press developers into dumping more logic into their procs.
Note that for any of these reasons - consider at least still testing your database logic, and refactoring your SQL scripts.
These "reasons" are probably a bad idea:
- Easy deployment - You can update a SQL script in production real quick! Just hope that the update doesn't itself have an error which accidentally screws all your production data. Also consider, why does the procedure need to be updated out-of-cycle in the first place? Was it something that would ideally have been abstracted out to a proper config file (whose whole point is to provide easy changes post-deployment)? Was it an error in the original logic, which could have been more easily prevented if it had been coded in a testable-friendly language like C#? Also, keep in mind that you can re-deploy a .Net assembly if you match its credentials (strong name, version, etc...), which is very doable given an automated build process.
- It's so much quicker to develop this way! Initially it may be faster to type the keystrokes, but the lack of testability and reusability will make the schedule get clobbered during maintenance.
In my personal experience, I see more data in the SP for the bad reasons ("it's real quick!")- the majority of the time it can be refactored out, to the benefit of the application and its development schedule.
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